swh.scheduler.backend module

swh.scheduler.backend.adapt_arrow(arrow)

swh.scheduler.backend.format_query(query, keys)

Format a query with the given keys

class swh.scheduler.backend.SchedulerBackend(db, min_pool_conns=1, max_pool_conns=10)

Bases: object

Backend for the Software Heritage scheduling database.

get_db()

put_db(db)

task_type_keys = ['type', 'description', 'backend_name', 'default_interval', 'min_interval', 'max_interval', 'backoff_factor', 'max_queue_length', 'num_retries', 'retry_delay']

create_task_type(task_type)

Create a new task type ready for scheduling.

Parameters

task_type (dict) –

a dictionary with the following keys:

• type (str): an identifier for the task type

• description (str): a human-readable description of what the task does

• backend_name (str): the name of the task in the job-scheduling backend

• default_interval (datetime.timedelta): the default interval between two task runs

• min_interval (datetime.timedelta): the minimum interval between two task runs

• max_interval (datetime.timedelta): the maximum interval between two task runs

• backoff_factor (float): the factor by which the interval changes at each run

• max_queue_length (int): the maximum length of the task queue for this task type

get_task_type(task_type_name)

Retrieve the task type with id task_type_name

get_task_types()

Retrieve all registered task types

get_or_create_lister(name: str, instance_name: Optional[str] = None) → swh.scheduler.model.Lister

Retrieve information about the given instance of the lister from the database, or create the entry if it did not exist.

update_lister(lister: swh.scheduler.model.Lister) → swh.scheduler.model.Lister

Update the state for the given lister instance in the database.

Returns

a new Lister object, with all fields updated from the database

Raises

StaleData if the updated timestamp for the lister instance in –

database doesn’t match the one passed by the user.

record_listed_origins(listed_origins: Iterable[swh.scheduler.model.ListedOrigin]) → List[swh.scheduler.model.ListedOrigin]

Record a set of origins that a lister has listed.

This performs an “upsert”: origins with the same (lister_id, url, visit_type) values are updated with new values for extra_loader_arguments, last_update and last_seen.

get_listed_origins(lister_id: Optional[uuid.UUID] = None, url: Optional[str] = None, limit: int = 1000, page_token: Optional[Tuple[uuid.UUID, str]] = None) → swh.scheduler.model.PaginatedListedOriginList

Get information on the listed origins matching either the url or lister_id, or both arguments.

task_create_keys = ['type', 'arguments', 'next_run', 'policy', 'status', 'retries_left', 'priority']

task_keys = ['type', 'arguments', 'next_run', 'policy', 'status', 'retries_left', 'priority', 'id', 'current_interval']

create_tasks(tasks, policy='recurring')

Create new tasks.

Parameters

tasks (list) –

each task is a dictionary with the following keys:

• type (str): the task type

• arguments (dict): the arguments for the task runner, keys:

  • args (list of str): arguments

  • kwargs (dict str -> str): keyword arguments

• next_run (datetime.datetime): the next scheduled run for the task

Returns

a list of created tasks.

set_status_tasks(task_ids, status='disabled', next_run=None)

Set the tasks’ status whose ids are listed.

If given, also set the next_run date.

disable_tasks(task_ids)

Disable the tasks whose ids are listed.

search_tasks(task_id=None, task_type=None, status=None, priority=None, policy=None, before=None, after=None, limit=None)

Search tasks from selected criterions

get_tasks(task_ids)

Retrieve the info of tasks whose ids are listed.

peek_ready_tasks(task_type, timestamp=None, num_tasks=None, num_tasks_priority=None)

Fetch the list of ready tasks

Parameters

• task_type (str) – filtering task per their type

• timestamp (datetime.datetime) – peek tasks that need to be executed before that timestamp

• num_tasks (int) – only peek at num_tasks tasks (with no priority)

• num_tasks_priority (int) – only peek at num_tasks_priority tasks (with priority)

Returns

a list of tasks

grab_ready_tasks(task_type, timestamp=None, num_tasks=None, num_tasks_priority=None)

Fetch the list of ready tasks, and mark them as scheduled

Parameters

• task_type (str) – filtering task per their type

• timestamp (datetime.datetime) – grab tasks that need to be executed before that timestamp

• num_tasks (int) – only grab num_tasks tasks (with no priority)

• num_tasks_priority (int) – only grab oneshot num_tasks tasks (with priorities)

Returns

a list of tasks

task_run_create_keys = ['task', 'backend_id', 'scheduled', 'metadata']

schedule_task_run(task_id, backend_id, metadata=None, timestamp=None)

Mark a given task as scheduled, adding a task_run entry in the database.

Parameters

• task_id (int) – the identifier for the task being scheduled

• backend_id (str) – the identifier of the job in the backend

• metadata (dict) – metadata to add to the task_run entry

• timestamp (datetime.datetime) – the instant the event occurred

Returns

a fresh task_run entry

mass_schedule_task_runs(task_runs)

Schedule a bunch of task runs.

Parameters

task_runs (list) –

a list of dicts with keys:

• task (int): the identifier for the task being scheduled

• backend_id (str): the identifier of the job in the backend

• metadata (dict): metadata to add to the task_run entry

• scheduled (datetime.datetime): the instant the event occurred

Returns

None

start_task_run(backend_id, metadata=None, timestamp=None)

Mark a given task as started, updating the corresponding task_run

entry in the database.

Parameters

• backend_id (str) – the identifier of the job in the backend

• metadata (dict) – metadata to add to the task_run entry

• timestamp (datetime.datetime) – the instant the event occurred

Returns

the updated task_run entry

end_task_run(backend_id, status, metadata=None, timestamp=None, result=None)

Mark a given task as ended, updating the corresponding task_run entry in the database.

Parameters

• backend_id (str) – the identifier of the job in the backend

• status (str) – how the task ended; one of: ‘eventful’, ‘uneventful’, ‘failed’

• metadata (dict) – metadata to add to the task_run entry

• timestamp (datetime.datetime) – the instant the event occurred

Returns

the updated task_run entry

filter_task_to_archive(after_ts: str, before_ts: str, limit: int = 10, page_token: Optional[str] = None) → Dict[str, Any]

Compute the tasks to archive within the datetime interval [after_ts, before_ts[. The method returns a paginated result.

Returns

• next_page_token: opaque token to be used as page_token to retrieve the next page of result. If absent, there is no more pages to gather.

• tasks: list of task dictionaries with the following keys:

  id (str): origin task id started (Optional[datetime]): started date scheduled (datetime): scheduled date arguments (json dict): task’s arguments …

Return type

dict with the following keys

delete_archived_tasks(task_ids)

Delete archived tasks as much as possible. Only the task_ids whose complete associated task_run have been cleaned up will be.

task_run_keys = ['id', 'task', 'backend_id', 'scheduled', 'started', 'ended', 'metadata', 'status']

get_task_runs(task_ids, limit=None)

Search task run for a task id

get_priority_ratios()